This paper develops a machine-learning method that allows researchers to estimate heterogeneous treatment effects with panel data in a setting with many covariates. Our method, which we name the dynamic causal forest (DCF) method, extends the causal-forest method of Wager and Athey (2018) by...

Based on administrative data of unemployed in Belgium, we estimate the labour market effects of three training programmes at various aggregation levels using Modified Causal Forests, a causal machine learning estimator. While all programmes have positive effects after the lock-in period, we find...

We study the long-term effects of a randomized intervention targeting children's socio-emotional skills. The classroom-based intervention for primary school children has positive impacts that persist for over a decade. Treated children become more likely to complete academic high school and...

We investigate regime-dependent Granger causality between real output, inflation and monetary indicators and map with U.S. Fed Chairperson's tenure since 1965. While all monetary indicators have causal predictive content in certain time periods, we report that the Federal Funds rate (FFR) and...

This paper estimates the causal effect of rural-urban migration on urban production in China. We use longitudinal data on manufacturing firms between 2001 and 2006 and exploit exogenous variation in rural-urban migration due to agricultural price shocks. Following a migrant inflow, labor costs...

We demonstrate that heat inhibits learning and that school air-conditioning mitigates this effect. Student fixed effects models using 10 million PSAT-retakers show hotter school days in years before the test reduce scores, with extreme heat being particularly damaging. Weekend and summer heat...

We present a general framework for Bayesian estimation and causality assessment in epidemiological models. The key to our approach is the use of sequential Monte Carlo methods to evaluate the likelihood of a generic epidemiological model. Once we have the likelihood, we specify priors and rely...

To investigate how Covid-19 is shaping the way Europeans think about institutions, we conducted a large online survey experiment during the first wave of the epidemic (June). With a randomised survey ow we varied whether respondents are given Covid-related treatment questions first, before...

We estimate the causal impact of countercyclical interest rates on macroeconomic outcomes in open economies. To identify countercyclical interest rates, we construct a new database of short-term interest rates, principal exports, and international commodity prices for 40 economies from 1870 to...

In this paper we study the finite sample and asymptotic properties of various weighting estimators of the local average treatment effect (LATE), several of which are based on Abadie (2003)’s kappa theorem. Our framework presumes a binary endogenous explanatory variable (“treatment”) and a...